Teaching
Chaminade University of Honolulu
Sample syllabi for Chaminade courses available through the syllabus repository.
CS-201: Programming in R
This course is an introduction to R that will cover the R topics and language. This course will include lectures, discussions, assignments, hands-on experiences with real data, and a project that could be used for future classes and investigation. This course will prepare students for the next data science courses and practice by providing students with knowledge, techniques, skills, and a data science mindset. Students in this course will learn the data science process of collecting, storing, and curating data; ingestion and wrangling data; R language; R used for database systems; analyzing data using R; visualizations; and reporting the results of the analysis.
Prerequisites: none
CS-301: Operating Systems
This course will introduce operating systems concepts, techniques, strategies, hardware and software, management, and virtualization. Students in this course will learn process management, memory management, I/O device management, file systems, distributed systems, security, and virtualization.
Prerequisites: EN-102 and COM-101
DS-300: Ethics Seminar
Seminar course following on and further developing concepts and skills in DS 200. Students will perform a service project in data ethics.
In this course, we will expand upon data ethics concepts discussed in DS 200, supplement discussions with case studies, and reinforce understanding with practical assignments.
Prerequisite: DS-200
DS-301: Community-Engaged Computing
Lecture course addressing the use of data analytics and visualization for evidence-based decision support across diverse organizations, with special reference to the potential impact of data-science mediated decision support on community, grassroots and social advocacy groups. Students will design community impact strategies based on stakeholder engagement, develop tools such as dashboards and story boards using relevant data sets and present outputs to the community constituents for the course.
Prerequisites: EN-102, COM-101 & DS-200
DS-303: Modeling for Prediction
This course provides an overview of the modeling and prediction process, including definition of goals for prediction, effective data preparation, algorithms, modeling methods and verification/validation. Students will learn iterative refinement of models based on a project in their special interest area.
Prerequisites: EN-102, COM-101, CS-201 or CS-202, MA-210, and MA-331
DS-357: Computational Linguistics
This course will introduce the use of computational and data-driven methods to analyze, understand, and process human language. Students will explore how language data can be represented, analyzed, and modeled using approaches from data science. The course will emphasize practical applications and the role of computational methods in understanding and working with language.
Prerequisites: EN-102 and COM-101.
DS-405: Advanced Programming I
Advanced skills in programming or learning an application.
In this course, students will learn to develop and deploy R packages.
Prerequisites: EN-102, COM-101, CS-201 or CS-202
DS-420: Foundations of Geospatial Thinking
This course introduces geographic perspectives that are foundational to Geographic Information Systems, including: human-environment interactions, spatial thinking, and systems thinking. Students will learn about the power of maps as communicative tools, and the ethical issues in the field of cartography. Key theoretical topics will include the spatial side of: systems, processes, distributions, clusters, movement, and networks with special attention to how cultural, biological, and earth systems interact. Students will interact with existing geographic data portals to explore topics in a region of interest to them. No previous experience in geography or data science is needed. This course will prepare students for any GIS course with the ability to think and communicate from geographic perspectives.
Prerequisites: EN-102 and COM-101.
DS-492: Capstone in Geospatial Intelligence
This course constitutes a culminating experience in the Geospatial Intelligence Certificate program (GEOINT). The course includes a semester project that demonstrates a GEOINT student’s skills and ability to apply advanced knowledge of geospatial principles. The project will involve a real-world problem using the GIS and remote sensing tools used in the curriculum. Students are encouraged to work collaboratively to develop and refine projects and to evaluate the ethical and professional aspects in this domain.
Prerequisites: DS-420, 421, 422, and 434 or consent
DS-495: Data Science Directed Research
This course is a research method and directed research course in data science. The course will include lectures, discussions, assignments used for the directed research project, and a semester long directed research project. The goal of the course has two parts: 1) students will be provided tools and techniques that will assist on assessing research designs and strategies to develop their data science directed research project and 2) students will execute and complete their data science directed research project. Students in this course will learn the different research methodologies; assess literature for a literature review; develop a research question or problem to analyze; learn data collection methods; learn sampling approaches; design and develop a proposal; apply knowledge, skills, and abilities from past data science courses; analyze and evaluate data; and produce a directed research product and communicate the project in front of technical and non-technical audiences.
Prerequisites: EN-102, COM-101, DS-301 & MA-331 and senior standing
University of Hawaiʻi at Mānoa (previously taught)
LING 102: Introduction to the Study of Language
Ling 102 is a 3-credit, 100-level non-technical introduction to linguistics, the scientific study of language. We talk about what makes language language and how students can begin to describe and analyze the languages and dialects spoken and heard around them. Major goals of this course include fostering an appreciation for linguistic and cultural diversity, and encouraging critical thinking through making connections between real-world observations, life experiences, and classroom knowledge. The course includes a Writing-Intensive focus, and includes projects and assignments designed to help students develop tools to use in future classes and employment: researching, writing, editing, working in groups, and clearly communicating ideas.
Some of the things students learn to do in this class include:
- learning to broadly transcribe American English words using the International Phonetic Alphabet (IPA)
- analyzing sentences in multiple languages in terms of grammatical relations and thematic roles
- reconstructing sounds and words in a proto-language, and
- presenting informed arguments about real-world events and attitudes related to linguistics and language
Sample Ling 102 syllabus (Fall 2019)
LING 420: Morphology
In Ling 420 we discuss various morphological phenomena and approaches to morphological issues, using examples from many languages. This course is designed to provide students with necessary knowledge and skills of morphological analysis, introduce morphological terms and major morphological phenomena, and demonstrate how morphology interacts with syntax and phonology. The class engages in morphological analysis regularly.
By the end of the course, students will be able to:
- define and discuss core notions related to morphology
- recognize and understand examples illustrating major morphological phenomena
- examine and compare morphological phenomena from a typological stance
- conduct and present morphological analyses of linguistic data
Familiarity with basic linguistics, including basic syntactic and phonological terminology, is assumed. The prerequisite for this course is Ling 320 (General Linguistics), but Ling 421 (Introduction to Phonological Analysis) and Ling 422 (Introduction to Grammatical Analysis) are recommended. Students who take Ling 420 are typically early graduate students or advanced undergraduates.